[en] Purpose: To investigate in three institutions, The Netherlands Cancer Institute (Antoni van Leeuwenhoek Huis [AvL]), Dr. Daniel den Hoed Cancer Center (DDHC), and Dr, Bernard Verbeeten Institute (BVI), how much the patient setup accuracy for irradiation of prostate cancer can be improved by an offline setup verification and correction procedure, using portal imaging. Methods and Materials: The verification procedure consisted of two stages. During the first stage, setup deviations were measured during a number (N_max) of consecutive initial treatment sessions. The length of the average three dimensional (3D) setup deviation vector was compared with an action level for corrections, which shrunk with the number of setup measurements. After a correction was applied, N_max measurements had to be performed again. Each institution chose different values for the initial action level (6, 9, and 10 mm) and N_max (2 and 4). The choice of these parameters was based on a simulation of the procedure, using as input preestimated values of random and systematic deviations in each institution. During the second stage of the procedure, with weekly setup measurements, the AvL used a different criterion ('outlier detection') for corrective actions than the DDHC and the BVI ('sliding average'). After each correction the first stage of the procedure was restarted. The procedure was tested for 151 patients (62 in AvL, 47 in DDHC, and 42 in BVI) treated for prostate carcinoma. Treatment techniques and portal image acquisition and analysis were different in each institution. Results: The actual distributions of random and systematic deviations without corrections were estimated by eliminating the effect of the corrections. The percentage of mean (systematic) 3D deviations larger than 5 mm was 26% for the AvL and the DDHC, and 36% for the BVI. The setup accuracy after application of the procedure was considerably improved (percentage of mean 3D deviations larger than 5 mm was 1.6% in the AvL and 0% in the DDHC and BVI), in agreement with the results of the simulation. The number of corrections (about 0.7 on the average per patient) was not larger than predicted. Conclusion: The verification procedure appeared to be feasible in the three institutions and enabled a significant reduction of mean 3D setup deviations. The computer simulation of the procedure proved to be a useful tool, because it enabled an accurate prediction of the setup accuracy and the required number of corrections

No abstract available

[en] Background and purpose: In the late 1990s a period of shortage of radiotherapy capacity caused long waiting times in The Netherlands. Investments in treatment vaults, equipment and training capacity were made. The developments since then are described and the actual situation is compared with the predictions throughout the years. Method and materials: Data are based on annual surveys on production, personnel and equipment of all 21 Dutch radiotherapy centers. Results: An annual increase in patients, radiotherapy treatments and a corresponding increase in equipment and personnel was seen, on average 3.5–4% per year. After an initial shift to more 3D conformal treatments, a subsequent change from 3D conformal to intensity modulated and image guided techniques was observed. There has been no increase in the number of radiotherapy centers and the average size of a Dutch department in 2010 was 5.7 linacs, 10.4 fte radiation oncologists, 4.8 fte physicists and 45.8 fte technologists. Conclusions: The number of linacs increased as anticipated. The increase in staffing was in balance with the need, resulting in only a limited number of vacancies. In 2010 there were virtually no waiting lists, and no overcapacity. The predicted need and the actual number of radiotherapy treatment series per year correspond very well. A national program for a planned increase of radiotherapy capacity is feasible. Expansion of existing departments instead of increasing the number allows for a more rapid introduction of new technologies and sufficient subspecialization of the staff

[en] In this study, computer-assisted analysis of prostate lesions was researched by combining information from two different magnetic resonance (MR) modalities: T2-weighted (T2-w) and dynamic contrast-enhanced (DCE) T1-w images. Two issues arise when incorporating T2-w images in a computer-aided diagnosis (CADx) system: T2-w values are position as well as sequence dependent and images can be misaligned due to patient movement during the acquisition. A method was developed that computes T2 estimates from a T2-w and proton density value and a known sequence model. A mutual information registration strategy was implemented to correct for patient movement. Global motion is modelled by an affine transformation, while local motion is described by a volume preserving non-rigid deformation based on B-splines. The additional value to the discriminating performance of a DCE T1-w-based CADx system was evaluated using bootstrapped ROC analysis. T2 estimates were successfully computed in 29 patients. T2 values were extracted and added to the CADx system from 39 malignant, 19 benign and 29 normal annotated regions. T2 values alone achieved a diagnostic accuracy of 0.85 (0.77-0.92) and showed a significantly improved discriminating performance of 0.89 (0.81-0.95), when combined with DCE T1-w features. In conclusion, the study demonstrated a simple T2 estimation method that has a diagnostic performance such that it complements a DCE T1-w-based CADx system in discriminating malignant lesions from normal and benign regions. Additionally, the T2 estimate is beneficial to visual inspection due to the removed coil profile and fixed window and level settings.

No abstract available

[en] In order to augment the certainty of the radiological interpretation of "possible microbleeds" after traumatic brain injury (TBI), we assessed their longitudinal evolution on 3-T SWI in patients with moderate/severe TBI. Standardized 3-T SWI and T1-weighted imaging were obtained 3 and 26 weeks after TBI in 31 patients. Their microbleeds were computer-aided detected and classified by a neuroradiologist as no, possible, or definite at baseline and follow-up, separately (single-scan evaluation). Thereafter, the classifications were re-evaluated after comparison between the time-points (post-comparison evaluation). We selected the possible microbleeds at baseline at single-scan evaluation and recorded their post-comparison classification at follow-up. Of the 1038 microbleeds at baseline, 173 were possible microbleeds. Of these, 53.8% corresponded to no microbleed at follow-up. At follow-up, 30.6% were possible and 15.6% were definite. Of the 120 differences between baseline and follow-up, 10% showed evidence of a pathophysiological change over time. Proximity to extra-axial injury and proximity to definite microbleeds were independently predictive of becoming a definite microbleed at follow-up. The reclassification level differed between anatomical locations. Our findings support disregarding possible microbleeds in the absence of clinical consequences. In selected cases, however, a follow-up SWI-scan could be considered to exclude evolution into a definite microbleed.

[en] Delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage (aSAH) can be reversible or progress to cerebral infarction. In patients with a deterioration clinically diagnosed as DCI, we investigated whether CT perfusion (CTP) can distinguish between reversible ischemia and ischemia progressing to cerebral infarction. From a prospectively collected series of aSAH patients, we included those with DCI, CTP on the day of clinical deterioration, and follow-up imaging. In qualitative CTP analyses (visual assessment), we calculated positive and negative predictive value (PPV and NPV) with 95 % confidence intervals (95%CI) of a perfusion deficit for infarction on follow-up imaging. In quantitative analyses, we compared perfusion values of the least perfused brain tissue between patients with and without infarction by using receiver-operator characteristic curves and calculated a threshold value with PPV and NPV for the perfusion parameter with the highest area under the curve. In qualitative analyses of 33 included patients, 15 of 17 patients (88 %) with and 6 of 16 patients (38 %) without infarction on follow-up imaging had a perfusion deficit during clinical deterioration (p = 0.002). Presence of a perfusion deficit had a PPV of 71 % (95%CI: 48-89 %) and NPV of 83 % (95%CI: 52-98 %) for infarction on follow-up. Quantitative analyses showed that an absolute minimal cerebral blood flow (CBF) threshold of 17.7 mL/100 g/min had a PPV of 63 % (95%CI: 41-81 %) and a NPV of 78 % (95%CI: 40-97 %) for infarction. CTP may differ between patients with DCI who develop infarction and those who do not. For this purpose, qualitative evaluation may perform marginally better than quantitative evaluation. (orig.)

[en] Tracer delay-sensitive perfusion algorithms in CT perfusion (CTP) result in an overestimation of the extent of ischemia in thromboembolic stroke. In diagnosing delayed cerebral ischemia (DCI) after aneurysmal subarachnoid hemorrhage (aSAH), delayed arrival of contrast due to vasospasm may also overestimate the extent of ischemia. We investigated the diagnostic accuracy of tracer delay-sensitive and tracer delay-insensitive algorithms for detecting DCI. From a prospectively collected series of aSAH patients admitted between 2007-2011, we included patients with any clinical deterioration other than rebleeding within 21 days after SAH who underwent NCCT/CTP/CTA imaging. Causes of clinical deterioration were categorized into DCI and no DCI. CTP maps were calculated with tracer delay-sensitive and tracer delay-insensitive algorithms and were visually assessed for the presence of perfusion deficits by two independent observers with different levels of experience. The diagnostic value of both algorithms was calculated for both observers. Seventy-one patients were included. For the experienced observer, the positive predictive values (PPVs) were 0.67 for the delay-sensitive and 0.66 for the delay-insensitive algorithm, and the negative predictive values (NPVs) were 0.73 and 0.74. For the less experienced observer, PPVs were 0.60 for both algorithms, and NPVs were 0.66 for the delay-sensitive and 0.63 for the delay-insensitive algorithm. Test characteristics are comparable for tracer delay-sensitive and tracer delay-insensitive algorithms for the visual assessment of CTP in diagnosing DCI. This indicates that both algorithms can be used for this purpose. (orig.)